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The mssql-python driver doesn't implement the callproc() method from the DB-API 2.0 specification. Calling callproc() raises NotSupportedError. Instead, use the ODBC {CALL ...} escape sequence with standard query execution methods.
Basic stored procedure execution
Without parameters
Execute a stored procedure by using the {CALL} escape sequence. This example calls the sp_databases system stored procedure, which takes no parameters and returns one row per database:
import mssql_python
conn = mssql_python.connect(connection_string)
cursor = conn.cursor()
cursor.execute("{CALL sp_databases}")
for row in cursor:
print(row.DATABASE_NAME, row.DATABASE_SIZE)
With input parameters
Pass parameters using positional or named placeholders:
# Single parameter
cursor.execute(
"{CALL dbo.uspGetManagerEmployees(?)}", (16,)
)
for row in cursor:
print(row.FirstName, row.LastName)
Output parameters
Declare and retrieve output parameters
SQL Server stored procedures can return values through output parameters. Use Transact-SQL (T-SQL) variables to capture output values, then retrieve them with a SELECT statement:
cursor.execute("""
DECLARE @total_out MONEY;
SELECT @total_out = SUM(TotalDue)
FROM Sales.SalesOrderHeader
WHERE CustomerID = %(customer_id)s;
SELECT @total_out AS TotalAmount;
""", {"customer_id": 29825})
row = cursor.fetchone()
total = row.TotalAmount
print(f"Customer total: ${total}")
Multiple output parameters
Capture multiple output values by declaring separate variables. The same pattern works with any stored procedure that has OUTPUT parameters:
cursor.execute("""
DECLARE @total_orders INT, @total_spent MONEY;
SELECT @total_orders = COUNT(*), @total_spent = SUM(TotalDue)
FROM Sales.SalesOrderHeader
WHERE CustomerID = %(cust_id)s;
SELECT @total_orders AS OrderCount, @total_spent AS TotalSpent;
""", {"cust_id": 29825})
stats = cursor.fetchone()
print(f"Orders: {stats.OrderCount}, Total spent: ${stats.TotalSpent}")
Return values
Capture stored procedure return value
Execute a stored procedure that returns results:
cursor.execute("EXECUTE dbo.uspGetEmployeeManagers @BusinessEntityID = %(emp_id)s", {"emp_id": 5})
rows = cursor.fetchall()
if rows:
print(f"Found {len(rows)} managers in chain")
for row in rows:
print(f" Manager: {row.FirstName} {row.LastName}")
else:
print("No managers found")
Return value with output parameters
cursor.execute("""
DECLARE @return_value INT, @message NVARCHAR(500);
SELECT @return_value = CASE WHEN COUNT(*) > 0 THEN 0 ELSE 1 END,
@message = CASE WHEN COUNT(*) > 0 THEN N'Customer found' ELSE N'Customer not found' END
FROM Sales.Customer WHERE CustomerID = %(cust_id)s;
SELECT @return_value AS ReturnCode, @message AS Message;
""", {"cust_id": 29825})
result = cursor.fetchone()
print(f"Return code: {result.ReturnCode}, Message: {result.Message}")
Result sets
Single result set
Execute a stored procedure that returns a single result set:
cursor.execute(
"{CALL dbo.uspGetBillOfMaterials(?, ?)}",
(800, "2026-01-01")
)
customers = cursor.fetchall()
for row in customers:
print(f"{row.ProductAssemblyID}: {row.ComponentDesc}")
Multiple result sets
Some stored procedures return multiple result sets. Use nextset() to navigate between them:
cursor.execute("""
SELECT TOP 1 SalesOrderID, OrderDate, TotalDue
FROM Sales.SalesOrderHeader WHERE CustomerID = 29825;
SELECT TOP 3 Name, ListPrice
FROM Production.Product WHERE ListPrice > 0
ORDER BY ListPrice DESC;
""")
# First result set: order header
order = cursor.fetchone()
print(f"Order: {order.SalesOrderID}, Date: {order.OrderDate}")
cursor.nextset()
# Second result set: products
print("Products:")
for item in cursor:
print(f" {item.Name}: ${item.ListPrice}")
Check for more result sets
Iterate through all result sets returned by a stored procedure using nextset():
cursor.execute("SELECT TOP 3 ProductID, Name FROM Production.Product; SELECT TOP 3 FirstName, LastName FROM Person.Person")
result_set_num = 1
while True:
print(f"--- Result Set {result_set_num} ---")
for row in cursor:
print(row)
if not cursor.nextset():
break
result_set_num += 1
Transactions with stored procedures
Explicit transaction control
Wrap multiple stored procedure calls in a transaction to ensure atomicity:
conn.autocommit = False
try:
cursor.execute("{CALL dbo.DebitAccount(?, ?)}", (1001, 100.00))
cursor.execute("{CALL dbo.CreditAccount(?, ?)}", (1002, 100.00))
conn.commit()
print("Transfer completed")
except mssql_python.DatabaseError as e:
conn.rollback()
print(f"Transfer failed: {e}")
Let stored procedure manage transaction
If the stored procedure handles its own transactions:
conn.autocommit = True # Let SP manage transactions
cursor.execute("""
DECLARE @result INT;
EXECUTE @result = dbo.TransferFunds
@FromAccount = %(from_acc)s,
@ToAccount = %(to_acc)s,
@Amount = %(amount)s;
SELECT @result AS TransferResult;
""", {"from_acc": 1001, "to_acc": 1002, "amount": 100.00})
result = cursor.fetchone()
if result.TransferResult == 0:
print("Transfer successful")
Error handling
Catch stored procedure errors
Handle exceptions raised by stored procedures or Transact-SQL statements:
try:
cursor.execute("{CALL dbo.DangerousProcedure}")
except mssql_python.ProgrammingError as e:
# Handle SQL errors raised by RAISERROR or THROW
print(f"Stored procedure error: {e}")
except mssql_python.DatabaseError as e:
# Handle other database errors
print(f"Database error: {e}")
Capture PRINT statements and informational messages
SQL Server PRINT statements and RAISERROR with severity below 11 are captured in cursor.messages after execution. Each entry is a (message_type, message_text) tuple. When a PRINT runs before a result set, it occupies a rowless result set of its own, so read cursor.messages first, then call nextset() to reach the rows:
cursor.execute("PRINT 'Operation complete'; SELECT 1 AS Status")
for msg_type, msg_text in cursor.messages:
print(f"Server message: {msg_text}")
cursor.nextset()
row = cursor.fetchone()
print(f"Status: {row.Status}")
When a stored procedure emits PRINT messages across multiple result sets, read cursor.messages after execute() and again after each nextset() call so messages from every result set are captured:
cursor.execute("""
PRINT 'Starting first result set';
SELECT TOP 3 ProductID, Name FROM Production.Product;
PRINT 'Starting second result set';
SELECT TOP 3 FirstName, LastName FROM Person.Person;
""")
all_messages = []
while True:
all_messages.extend(cursor.messages)
if cursor.description:
for row in cursor:
print(row)
if not cursor.nextset():
break
for _, text in all_messages:
print(f"Server: {text}")
For the full cursor.messages API, see Cursor management.
Best practices
Use named parameters
Named parameters are clearer and maintain order independence:
# Recommended: {CALL} with positional parameters
cursor.execute(
"{CALL dbo.uspGetBillOfMaterials(?, ?)}",
(800, "2026-01-01")
)
# Also valid: EXECUTE with named T-SQL parameters
cursor.execute("""
EXECUTE dbo.uspGetBillOfMaterials
@StartProductID = ?,
@CheckDate = ?
""", (800, "2026-01-01"))
Handle nullable output parameters
Check for NULL values when retrieving output parameters from stored procedures:
cursor.execute("""
DECLARE @optional_value NVARCHAR(100);
SELECT @optional_value = Color FROM Production.Product WHERE ProductID = %(id)s;
SELECT @optional_value AS OutputValue;
""", {"id": 1})
result = cursor.fetchone()
if result.OutputValue is not None:
print(f"Value: {result.OutputValue}")
else:
print("No value returned")
Use SET NOCOUNT ON in stored procedures
For better performance and cleaner result handling, ensure your stored procedures include:
CREATE PROCEDURE dbo.MyProcedure
AS
BEGIN
SET NOCOUNT ON; -- Prevents "n rows affected" messages
-- procedure logic
END
Example: Complete workflow
Here's a practical example that calls a stored procedure, retrieves output values, and handles errors:
import mssql_python
def get_employee_report(manager_id: int) -> dict:
"""Look up a manager's employees and compute average vacation hours."""
conn = mssql_python.connect(connection_string)
conn.autocommit = False
cursor = conn.cursor()
try:
# Get manager info
cursor.execute("""
SELECT BusinessEntityID, JobTitle
FROM HumanResources.Employee
WHERE BusinessEntityID = %(mgr)s
""", {"mgr": manager_id})
mgr = cursor.fetchone()
print(f"Manager {mgr.BusinessEntityID}: {mgr.JobTitle}")
# Get direct reports via stored procedure
cursor.execute("{CALL dbo.uspGetManagerEmployees(?)}", (manager_id,))
employees = cursor.fetchall()
print(f"Found {len(employees)} employee(s)")
# Compute average vacation hours
cursor.execute("""
DECLARE @avg_hours INT;
SELECT @avg_hours = AVG(VacationHours)
FROM HumanResources.Employee;
SELECT @avg_hours AS AvgVacation;
""")
avg = cursor.fetchone().AvgVacation
print(f"Avg vacation hours: {avg}")
conn.commit()
return {"manager": mgr.JobTitle, "reports": len(employees), "avg_vacation": avg}
except mssql_python.DatabaseError as e:
conn.rollback()
raise
finally:
cursor.close()
conn.close()
# Usage
result = get_employee_report(manager_id=16)
Get generated keys by using OUTPUT INSERTED
To retrieve an identity value from an INSERT (with or without a stored procedure), use OUTPUT INSERTED instead of SCOPE_IDENTITY(). This approach returns the value in the same result set:
cursor.execute("""
INSERT INTO Production.ProductCategory (Name)
OUTPUT INSERTED.ProductCategoryID
VALUES (%(name)s)
""", {"name": "Custom Parts"})
new_id = cursor.fetchval()
print(f"New category ID: {new_id}")
This pattern works for any table with an identity column and doesn't require a stored procedure.
Unsupported features
callproc()
The mssql-python driver raises NotSupportedError if you call cursor.callproc(). Use cursor.execute("{CALL ...}") or cursor.execute("EXECUTE ...") instead, as shown throughout this article.
Table-valued parameters (TVPs)
Table-valued parameters aren't supported in the current version (1.12.0) of mssql-python. If you need to pass a set of rows to a stored procedure, use alternatives:
- Insert into a temp table first, then have the stored procedure read from it.
- Use
bulkcopy()to load data into a staging table. - Pass a JSON string and parse it with
OPENJSONinside the procedure.